Cancer Clinical Trials: Companion Diagnostics or Gene Sequencing?

Last year saw some interesting developments from MD Anderson Cancer Center in early phase clinical trials that may have a far-reaching impact on the future of cancer research as we know it:

At ASCO in June, Dr Tsimberidou presented the initial results from a phase I study run by the MD Anderson Department of Investigational Cancer Therapeutics group. Instead of testing patients with a given cancer (eg lung) for individual mutations eg ALK or EGFR and then offering patients a targted drug as we normally do, they ran a broad diagnostic panel across a multitude of patients with different cancers to determine what the tumour was telling them about the aberrations and selected appropriate targeted therapies. While the study was small in size, the results were better than random selection.

In September at the ECCO meeting in Stockholm, Dr Gordon Mills (Head of Systems Biology) stated in his keynote presentation that 30,000 cancer patients at MD Anderson would be screened and tested for aberrations using gene sequencing. This has huge implications for clinical trial efficiency, since they will effectively generate a powerful database that will enable them to match patients to studies based on the precise selection criteria, rather than looking at a protocol and testing new patients that subsequently come in the door for each target individually.

The other thing that many readers have asked about is companion diagnostics and whether they are the future following the recent approvals of crizotinib (Xalkori) and vemurafenib (Zelboraf) in ALK+ lung cancer and BRAFV600E melanoma respectively?

More recently, we have seen numerous papers discussing the findings from massive parallel sequencing studies (more on that tomorrow) and developments in gene sequencing, including a dramatic announcement from Oxford Nanopore on Friday regarding its novel third generation sequencing progress.

I decided to discuss these issues with Dr Razelle Kurzrock, who heads up the Department of Investigational Cancer Therapeutics group at MD Anderson. Here’s the transcript of the interview. Please do check out the brief audio clip too, as this highlights a very important trend for the future with gene sequencing costs/time coming down.

PSB: Could you tell us a bit more about your phase I group and what you are doing with regards to matching therapies to targets?

Dr Kurzrock: Essentially we do phase 1 studies, which can be anything from new first in human drugs that are just going from animals to patients, or really any other phase 1. It might be in experimental drugs, or new combinations of two experimental drugs, combinations of an experimental and an FDA approved drug or combinations of FDA approved drugs. It is any new study that is just a new way of looking drugs is considered phase 1. That is really what we are doing. It is sort of a large scale, we have about 128 studies and we put over 1100 patients on study last year.

But I don’t think that has really gotten people interested or that we really are at the point that we are most excited about. The idea is to do molecular profiling on patients as they come in the door, then to try to match them with the appropriate targeted drugs. Of course people have done this for individual studies, like the ALK inhibitor crizotinib, the investigators and the company looked for ALK rearranged lung cancer patients.

The thing that we are doing differently is that we are not looking for one abnormality to match with one drug. We are looking at a panel of abnormalities as patients come in the door and then decide which drug to match them to. So it is a more generalized type of way of doing things and I am sure it is the way things will be done in the community in the future. It is a really simple concept, but nobody has done it like this before.

PSB: If you have more than one abnormality will you consider combination therapy or just target the main mutation first?

Dr Kurzrock: Well, I think it is either one. If you have more than one abnormality you can consider combinations or you can try and figure out what the main one is. The concept of looking for multiple abnormalities at once is really a diagnostic concept.

As an example if you had lung cancer, we know that there is ALK rearrangement in 4% of patients, then there might be an EGFR mutation in 5% of patients and probably when we look at al lung cancer there might be 20 different mutations, subsets of patients. There may be 50, we don’t know all of them yet.

This inevitably has implications of how we test and screen patients for clinical trials, as Dr Kurzrock astutely observed in the sound bite below:

PSB: I like the idea of doing the panel, and with over 100 studies, it must make it more efficient to assign patients to the appropriate clinical trials?

Dr Kurzrock: I think it is a lot more efficient. With the caveat that this was not a randomized study, what we saw in our pilot study was that we were getting response rates that were considerably higher than what we would expect in phase 1.

Our background response rates are about 5% of our patients will get a complete or partial remission if we just do things the old way, remembering that phase 1 patients are patients that have by definition failed all therapy. They are often in good shape, but have a highly resistant and lethal tumor.

But the response rates when we did the matching was 27%. Again, this isn’t a non-randomized trial so there are biases, but it could be actually biases that might lower the response rate or biases that might raise the response rates. But the bottom line is that it was much higher than what we would have anticipated. This of course needs to undergo more rigorous testing, but we were impressed that doing this was better for our patients and actually better for drug development.

PSB: So are you using next generation sequencing to drive your diagnostic panel?

Dr Kurzrock: That’s a good question. This is an area in very rapid flux. When we presented our data at ASCO 2011, we presented first generation data where we were just doing a very small panel of mutational analysis. Essentially we presented in mid 2011, data from 2010 mainly and the field has moved so quickly. The data was especially impressive because we used this primitive, first generation way of doing things. We are now expanding to using a Sequenom panel which looks at multiple different mutations, and I think the next generation panel is going to be the one that comes on line pretty soon. All exomic sequencing, while it can be done, the bioinformatics is still complicated and that is probably not quite ready yet. I think it will be ready maybe in a year or two years, but I think that is not quite ready to be used on large volumes of patients. But, Next Gen Sequencing, although you use the methodology, you only pick a set number of genes say 300, that is probably useable at this point.

PSB: I remember talking to Gordon Mills at ECCO and he said as the cost of sequencing costs come down, the analytical costs are going to go through the roof because it gets more and more complicated.

Dr Kurzrock: The analytical costs are now the problem. But, where I disagree is having seen how rapidly this field moves, what we need now is a jump in analytical capability. So if we assume there is not going to be a jump in knowledge, it is going to go through the roof.

I have a different assumption, I think there will be a leap. People are working on this. There is going to be a leap in the way we do things. We are going to be able to do the bioinformatics very quickly and the costs will come down just like the costs of sequencing.

In the early 1990s, I remember when everybody who knew anything said we would never sequence the human genome because it was too complicated. Then by the late 1990s we had sequenced the human genome, but it cost $3Billion dollars to sequence a patient. Now it costs $5000 and one company has said they will do it for $1000. This took leaps in technology that have occurred extraordinarily rapidly in 10 or 12 years. I absolutely think those leaps will occur in bioinformatics now, which is the sticking point.

PSB: Many oncology pharma companies seen to be going down the route of developing a companion diagnostic test with a targeted therapy e.g. crizotinib and vemurafenib, but I’m wondering is that really the way of the future?

Dr Kurzrock: I think that is not the way of the future, for the reason that I said. It is an interesting thing, the diagnostic panel is a great idea, but technology is moving so fast now that the diagnostic test is going to be outmoded, if it is not already outmoded.

And it is for the reason that I mentioned. A patient walks in the door, you can not see if that patient has whatever type of cancer whether it be breast cancer or lung cancer or whatever, you can not tell by look looking at that patient which diagnostic panel to do. You just can’t know. In essence you can choose to do one diagnostic test but that will probably be 4% of patients with that disease. So what you are going to have to do is multiple diagnostic tests to cover all the realms of possibility. If you license diagnostic tests one at a time and I have to do 20 or 50 or whatever tests, it is going to be hugely expensive, plus probably you will run out of tissue and you will have to rebiopsy the patient.

To me the way of the future will be a multi-assay panel whether it is Sequenom or next gen sequencing, probably it will be next gen sequencing or something like that, that will look at all the possible aberrations, rather than looking at them one at a time. Ultimately it is going to run up the cost if we do it that way [with individual diagnostic tests].

PSB: If we want to help more patients then we have to figure out what the aberrations are?

Dr Kurzrock: I think in the most simple sense, this is simply diagnosis. The reason we diagnose patients and we try to figure out whether you have breast cancer, you have lung cancer or colon cancer or some other cancer, is in order to give you the best treatment. That is the reason we give you a diagnosis, also to tell you the prognosis, but we want to tell you your best treatment.

Up till now, we the way we have diagnosed patients is with a light microscope that was invented back in 1590. In the simplest sense this is just a more sophisticated way of diagnosing patients, and it as at the molecular level. It is like using a molecular microscope except the molecular microscope is Next Gen Sequencing. So we really want to know when a patient walks in the door, what do you have, what is your disease at a molecular level? You can’t do that by using one probe at time, you have to look at all the relevant gene abnormalities and then figure out which one is abnormal.

In summary…

There is no doubt in my mind that broad molecular gene profiling (or massively parallel sequencing as it is often called in research) to find aberrations in the tumours of cancer patients will be:

Faster

More effective

for patient clinical trial selection than the current approach of biopsies for individual targets based on a single diagnostic test. If we want to speed up clinical trials a broader screening approach will no doubt be a better starting point than searching for small needles in a haystack.

That said, the challenges going forward are still many. These include greater analytical and bioinformatic costs, as well as figuring out which aberrations really matter. After all, some will be drivers, but many will be passengers that merely add noise to the signal, so targeting every aberration that appears in a panel may not actually have any effect clinically and may even induce unwanted systemic side effects.

Until we determine which aberrations are the critical targets in each tumour type or subtype, as well as identify those that develop in response to therapy (adaptive resistance), then we still have a long way to go in terms of improving our understanding of the biology underlying the many diseases that make up ‘cancer’ and improving patient outcomes with therapeutic interventions.

Nice article. The ‘r’ in Dr. Kurzrock’s name is missing in the answers.

http://pharmastrategyblog.com maverickny

Fixed – good catch!

http://twitter.com/biotechbaumer Jonathan Mandelbaum

Very exciting times for oncology drug dev! Completely agree that the understanding what the drivers/passengers in every given tumor type will be key to this approach. There are already examples that drivers in one type of cancer may not necessarily behave the same way in other tumor types (eg. in your previous post on de novo resistance to BRAFi in V600E CRC). Unfortunately teasing apart the functional consequences of all these mutations will take MANY years of academic research using in vitro systems, mouse models, etc…The cancer revolution has begun but unfortunately it will not happen overnight.

http://pharmastrategyblog.com maverickny

Agreed it will take a long time but the good news is that finally we are making some progress on the complex networks and starting to tease out a few drivers and also the causes of primary and secondary resistance. You’ve just reminded me of something else I meant to post on in breast cancer – stay tuned!

Docnuman

Insightful and useful article

http://pharmastrategyblog.com maverickny

Hi Doc! Good to see you back, hope all is well. Hope to catch you at ASCO this year…

cmschultes

Very interesting article.

As someone working on a compound that will be submitted together with a companion diagnostic, however, I would say that it reflects strongly the scientific questions and developments over the past two decades. My feeling is that the regulators and in general the pharma community is not ready (and will not be for some time) to deal with the huge amounts of data that will be generated in this way. There is still a strong adherence to standards, guidelines, etc., and individualising therapy in the way suggested (which really does make every patient’s tumour unique) will present a big challenge with categorising, grouping, and analysing (as well as testing) tumours in order to know what to treat them with.

Plus the analysis is one thing, the therapeutic tools another: how much more do we need to know about drug mechanism of action to match the fine level of genetic detail we will have!? Sounds a bit to me like creating a pointilist painting with a big fat brush… (imagine Rothko meeting Seurat!).

Not to want to sound pessimistic, there is always a push-pull between the science and the tools, and it will be interesting to see how institutions like MDACC and pharma companies can meet in the middle to advance the field.

http://pharmastrategyblog.com maverickny

Hi there, I can understand entirely where Pharma is coming from having been involved with the development of a drug (Gleevec) with a diagnostic (KIT/cd117) in GIST. Intuitively is makes sense to screen for appropriate patients and match them to a targeted therapy. However, Dr Kurzrock is correct in that this is a very wasteful and inefficient approach. Eventually, I think there will be a middle ground as sequencing costs and analysis come down, making that approach more useful.

cmschultes

Hi, I completely agree! It’s interesting to see it this way of course, because the Tx/CDx debate is one that is billed as “cutting-edge” but seems likely to be overhauled by the advances in sequencing you mention before it even becomes properly established (I think).

I was just trying to highlight what a discrepancy I see between the fine-grained detail we are likely to have from the biology, compared to the blunt tools that are our drugs. Up to us to finetune the molecules a little more, trying to make more subtle keys for the intricate locks…